https://github.com/farfarfun/fundata
数据处理工具包 - 提供数据清洗、转换和分析功能
https://github.com/farfarfun/fundata
data-analysis data-processing farfarfun numpy pandas python
Last synced: 4 months ago
JSON representation
数据处理工具包 - 提供数据清洗、转换和分析功能
- Host: GitHub
- URL: https://github.com/farfarfun/fundata
- Owner: farfarfun
- Created: 2019-05-24T01:53:23.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2024-12-02T07:13:05.000Z (over 1 year ago)
- Last Synced: 2025-10-26T21:33:21.483Z (8 months ago)
- Topics: data-analysis, data-processing, farfarfun, numpy, pandas, python
- Language: Python
- Homepage: https://pypi.org/project/fundata/
- Size: 21.5 KB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# notedata
在学习和工作过程中，经常用到一些比较通用的数据集，很多是国外的数据集，下载很慢。
这里整理一些数据，并转存到蓝奏云，如果后续有免费的公有云，也可以再迁移到其他云盘。
|序号|分类|名称|描述|官网下载|蓝奏下载|
|:-:|:-:|:-:|:-:|:-:|:-:|
|0|dataset|iris|iris数据集|[官网链接](https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data)|暂无|
|1|dataset|electronics-reviews|Amazon评论数据|[官网链接](http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/reviews_Electronics_5.json.gz)|[蓝奏链接](https://wws.lanzous.com/b01hkzfuj)|
|2|dataset|electronics-meta|Amazon评论数据|[官网链接](http://snap.stanford.edu/data/amazon/productGraph/categoryFiles/meta_Electronics.json.gz)|[蓝奏链接](https://wws.lanzous.com/b01hqeora)|
|3|dataset|movielens-100k|包含用户对电影的评级数据、电影元数据信息和用户属性信息|[官网链接](http://files.grouplens.org/datasets/movielens/ml-100k.zip)|[蓝奏链接](https://wws.lanzous.com/iyykCfbi64j)|
|4|dataset|movielens-1m|包含用户对电影的评级数据、电影元数据信息和用户属性信息|[官网链接](http://files.grouplens.org/datasets/movielens/ml-1m.zip)|[蓝奏链接](https://wws.lanzous.com/ihoSUfbi65a)|
|5|dataset|movielens-10m|包含用户对电影的评级数据、电影元数据信息和用户属性信息|[官网链接](http://files.grouplens.org/datasets/movielens/ml-10m.zip)|[蓝奏链接](https://wws.lanzous.com/iXvEmfbi6di)|
|6|dataset|movielens-20m|包含用户对电影的评级数据、电影元数据信息和用户属性信息|[官网链接](http://files.grouplens.org/datasets/movielens/ml-20m.zip)|[蓝奏链接](https://wws.lanzous.com/b01hkt17g)|
|7|dataset|movielens-25m|包含用户对电影的评级数据、电影元数据信息和用户属性信息|[官网链接](http://files.grouplens.org/datasets/movielens/ml-25m.zip)|[蓝奏链接](https://wws.lanzous.com/b01hkt24j)|
|8|dataset|adult-train||[官网链接](https://raw.githubusercontent.com/1007530194/data/master/recommendation/data/adult.data.txt)|暂无|
|9|dataset|adult-test||[官网链接](https://raw.githubusercontent.com/1007530194/data/master/recommendation/data/adult.test.txt)|暂无|
|10|dataset|porto-seguro-train||[官网链接](https://raw.githubusercontent.com/1007530194/data/master/recommendation/data/porto_seguro_train.csv)|暂无|
|11|dataset|porto-seguro-test||[官网链接](https://raw.githubusercontent.com/1007530194/data/master/recommendation/data/porto_seguro_test.csv)|暂无|
|12|dataset|bitly-usagov||[官网链接](https://raw.githubusercontent.com/1007530194/data/master/datasets/bitly_usagov/example.txt)|暂无|
|13|dataset|coco-val2017|大型图像数据集, 用于对象检测、分割、人体关键点检测、语义分割和字幕生成|[官网链接](http://images.cocodataset.org/zips/val2017.zip)|[蓝奏链接](https://wws.lanzous.com/b01hkb8fi)|
|14|dataset|coco-annotations_trainval2017|大型图像数据集, 用于对象检测、分割、人体关键点检测、语义分割和字幕生成|[官网链接](http://images.cocodataset.org/annotations/annotations_trainval2017.zip)|[蓝奏链接](https://wws.lanzous.com/b01hkb86j)|
|15|model|yolov3.weight|yolov3模型的权重|暂无|[蓝奏链接](https://wws.lanzous.com/b01hjn3ih)|
|16|model|yolov3.h5|yolov3模型的权重|暂无|[蓝奏链接](https://wws.lanzous.com/b01hjn3aj)|
|17|model|yolov4.weight|yolov4模型的权重|暂无|[蓝奏链接](https://wws.lanzous.com/b01hjn3yd)|
|18|model|yolov4-416.h5|yolov4模型的权重|暂无|[蓝奏链接](https://wws.lanzous.com/b01hl9lej)|
|19|dataset|criteo-sample|criteo_sample数据集|[官网链接](https://raw.githubusercontent.com/shenweichen/DeepCTR/master/examples/criteo_sample.txt)|[蓝奏链接](https://wws.lanzous.com/ihLhrhejkxi)|
|20|dataset|criteo-kaggle|criteo-kaggle数据集|[官网链接](https://s3-eu-west-1.amazonaws.com/kaggle-display-advertising-challenge-dataset/dac.tar.gz)|[蓝奏链接](https://wws.lanzous.com/b01hqh97i)|
注：蓝奏无法上传大于100MB的数据，将一个数据拆分为多个文件上传，必须用[notedrive](https://github.com/notechats/notedrive) 来下载
# 感谢
感谢蓝奏云